{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f1461e7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import time\n",
    "import re\n",
    "import os\n",
    "from tqdm.notebook import tqdm\n",
    "import tushare as ts\n",
    "from datetime import datetime, timedelta\n",
    "from dateutil.relativedelta import relativedelta\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "token = '1501ffe708345cffa38d9bbc0bd371e93b4b7412e7a8e1f811d3c442'\n",
    "ts.set_token(token)\n",
    "pro = ts.pro_api(token)\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] \n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "\n",
    "from funcs import *\n",
    "期货前缀ss = get_期货前缀ss(False)\n",
    "df_所有合约 = get_df_所有合约()\n",
    "code_delist_date_dict = get_code_delist_date_dict(df_所有合约)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5aa1e051",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a854b111",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "887ee0114491450a91feec4c664d6c06",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/77 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d9e999af8d8540a582f16de9226ba859",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/4 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f08b73ac3bce4541aa1df723a57566b6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/4 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "字母s = []\n",
    "最新价格s = []\n",
    "for 期货前缀 in tqdm(期货前缀ss):\n",
    "    df = get_df(期货前缀)\n",
    "    dd_amount = df.pivot(index='t',columns='code',values='amount')\n",
    "    df_close = df.pivot(index='t', columns='code', values='close')\n",
    "    当前主力代码 = pd.Series(dd_amount.columns[np.argsort(-dd_amount.values,axis=1)[:,0]],index=dd_amount.index).shift(1)\n",
    "    最新价格 = df_close.apply(lambda x: x.get(当前主力代码.get(x.name)), axis=1).dropna()[-1]\n",
    "    字母s.append(期货前缀)\n",
    "    最新价格s.append(最新价格)\n",
    "    \n",
    "最新价格字典 = dict(zip(字母s,最新价格s))\n",
    "\n",
    "dd_qty_param = pd.read_csv('basicdata/qty_param.csv',index_col=0)\n",
    "dd_qty_param['symbol'] = dd_qty_param.index\n",
    "dd_qty_param['symbol_x'] = dd_qty_param.index.to_series().apply(lambda x:x.upper())\n",
    "dd_qty_param.index = dd_qty_param.index.to_series().apply(lambda x:x.upper())\n",
    "dd_qty_param['price'] = dd_qty_param['symbol_x'].apply(lambda x:最新价格字典.get(x))\n",
    "dd_qty_param['per_margin'] = dd_qty_param['multiplier']*dd_qty_param['price']\n",
    "\n",
    "期货前缀ss = ['IH','IF','IC','IM']\n",
    "字母s = list(set(字母s) & set(dd_qty_param.index))\n",
    "pp0, pp1 = get_pp_dict(期货前缀ss)\n",
    "ddds = []\n",
    "for 期货前缀 in tqdm(期货前缀ss):\n",
    "    ddd = get_ddd(期货前缀,code_delist_date_dict,pp0,pp1)\n",
    "    ddds.append(ddd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "afc24f83",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_收益率 = pd.concat([ddds[0]['收益率0'],ddds[1]['收益率0'],ddds[2]['收益率0']],axis=1)\n",
    "df_收益率.columns = ['IH','IF','IC']\n",
    "\n",
    "df_基差率 = pd.concat([ddds[0]['基差率01'],ddds[1]['基差率01'],ddds[2]['基差率01']],axis=1)\n",
    "df_基差率.columns = ['IH','IF','IC']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0a993359",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_因子日度收益2(因子, 因子名, 收益率, ttp):\n",
    "    tt = 因子.rank(1) == 3\n",
    "    bb = 因子.rank(1) == 1\n",
    "\n",
    "    做多的品种 = tt if ttp == 1 else bb\n",
    "    做空的品种 = tt if ttp == -1 else bb\n",
    "    收益s = []\n",
    "    for i in range(len(因子) - 1):\n",
    "        s_date = 因子.index[i]\n",
    "        e_date = 因子.index[i + 1]\n",
    "        当期做多 = 做多的品种.loc[s_date].index[做多的品种.loc[s_date]]\n",
    "        当期做空 = 做空的品种.loc[s_date].index[做空的品种.loc[s_date]]\n",
    "        做多收益 = 收益率[当期做多][s_date + timedelta(days=1):e_date].mean(1) * 1\n",
    "        做空收益 = 收益率[当期做空][s_date + timedelta(days=1):e_date].mean(1) * -1\n",
    "        收益 = (做多收益 + 做空收益) / 2\n",
    "        # 收益 = 做多收益\n",
    "        收益s.append(收益)\n",
    "    rr = pd.concat(收益s)\n",
    "    rr.name = 因子名\n",
    "    return rr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c7236551",
   "metadata": {},
   "outputs": [],
   "source": [
    "rr = get_因子日度收益2(df_基差率.rolling(120).mean().resample('M').last(), 'x', df_收益率, -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4440c1c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.DataFrame(rr).to_csv('股指策略x.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8eb6fd7e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a1d4d06b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7635b538",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "b738d787",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='t'>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sell = df_基差率.rolling(120).mean().resample('M').last().rank(1) == 3\n",
    "buy = df_基差率.rolling(120).mean().resample('M').last().rank(1) == 1\n",
    "ret = df_收益率.resample('M').sum().shift(-1)*buy - df_收益率.resample('M').sum().shift(-1)*sell\n",
    "ret = ret.sum(1)/2\n",
    "\n",
    "ret2 = df_收益率.resample('M').sum().shift(-1)['IF'] - df_收益率.resample('M').sum().shift(-1)['IH']\n",
    "ret['2020-01-01':].cumsum().plot()\n",
    "ret2['2020-01-01':].cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "a045191a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "t\n",
       "2010-04-30   -0.112467\n",
       "2010-05-31   -0.083214\n",
       "2010-06-30    0.107224\n",
       "2010-07-31    0.010221\n",
       "2010-08-31    0.012176\n",
       "                ...   \n",
       "2024-03-31   -0.000196\n",
       "2024-04-30   -0.006254\n",
       "2024-05-31   -0.004959\n",
       "2024-06-30   -0.009915\n",
       "2024-07-31         NaN\n",
       "Freq: ME, Length: 172, dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rr2 = df_收益率.resample('M').sum().shift(-1)['IF'] - df_收益率.resample('M').sum().shift(-1)['IH']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1328036d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "969101da",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.5483870967741935, 0.41935483870967744)"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "the_date = '2022-01-01'\n",
    "(ret[the_date:] > 0).mean(),(ret2[the_date:] > 0).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "2726675a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1.351523633247204, 1.127588272768948)"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "abs(ret[the_date:][ret[the_date:]>0].mean()/ret[the_date:][ret[the_date:]<0].mean()),\\\n",
    "abs(ret2[the_date:][ret2[the_date:]>0].mean()/ret2[the_date:][ret2[the_date:]<0].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3883d3c",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7530d54d",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "cea1e2a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IF    89\n",
       "IC    47\n",
       "IH    36\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(buy*1).idxmax(1).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d09c37be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IH    95\n",
       "IC    46\n",
       "IF    31\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(sell*1).idxmax(1).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e0e24d8",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "df045cdc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ac1b54c9",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "1a19d19c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='trade_date'>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "the_date = '2010-01-01'\n",
    "费率 = 0.0003\n",
    "\n",
    "code = '000300.SH'\n",
    "dd = pro.index_daily(ts_code=code)\n",
    "dd.index = pd.to_datetime(dd['trade_date'])\n",
    "dd = dd[['open','high','low','close']]\n",
    "dd = dd.sort_index()\n",
    "dd['pct'] = dd['close'].pct_change()\n",
    "dd['weekday'] = [x.weekday() for x in dd.index]\n",
    "\n",
    "sig1 = (dd['high'] + dd['low'] > dd['open'] + dd['close']).apply(lambda x:1 if x else -1)\n",
    "fee1 = sig1.diff().abs()*费率\n",
    "ret1 = sig1*dd['pct'].shift(-1) - fee1\n",
    "ret1 = ret1[the_date:]\n",
    "ret1.cumsum().plot(figsize=(14,6),grid=True)\n",
    "\n",
    "\n",
    "sig2 = (((dd['open'] - dd['close'].shift(1))/(dd['close'].shift(1))).rolling(4).mean() > 0).apply(lambda x:1 if x else -1)\n",
    "sig2 = sig2*(dd['weekday'] == 4) # 只取周五的信号\n",
    "fee2 = sig2.diff().abs()*费率\n",
    "ret2 = sig2*dd['pct'].shift(-1) - fee2\n",
    "ret2 = ret2[the_date:]\n",
    "ret2.cumsum().plot(figsize=(14,6),grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2f6e8a79",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "40b0eac7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5495905368516834"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(ret1 > 0).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "2cf12b4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.5725938009787929, 1.0465370079058627)"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "the_date = '2022-01-01'\n",
    "(ret1[the_date:] > 0).mean(),\\\n",
    "abs(ret1[the_date:][ret1[the_date:]>0].mean()/ret1[the_date:][ret1[the_date:]<0].mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "60b31933",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0308657084204436"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(250**0.5)*ret1.mean()/ret1.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "ca130114",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pct</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>994.7690</td>\n",
       "      <td>994.7690</td>\n",
       "      <td>980.6580</td>\n",
       "      <td>982.7940</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>981.5770</td>\n",
       "      <td>997.3230</td>\n",
       "      <td>979.8770</td>\n",
       "      <td>992.5640</td>\n",
       "      <td>0.009941</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>993.3310</td>\n",
       "      <td>993.7880</td>\n",
       "      <td>980.3300</td>\n",
       "      <td>983.1740</td>\n",
       "      <td>-0.009460</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>983.0450</td>\n",
       "      <td>995.7110</td>\n",
       "      <td>979.8120</td>\n",
       "      <td>983.9580</td>\n",
       "      <td>0.000797</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-10</th>\n",
       "      <td>983.7600</td>\n",
       "      <td>993.9590</td>\n",
       "      <td>979.7890</td>\n",
       "      <td>993.8790</td>\n",
       "      <td>0.010083</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-10</th>\n",
       "      <td>3425.8818</td>\n",
       "      <td>3447.5050</td>\n",
       "      <td>3423.6483</td>\n",
       "      <td>3428.9657</td>\n",
       "      <td>-0.003153</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-11</th>\n",
       "      <td>3451.0442</td>\n",
       "      <td>3473.9837</td>\n",
       "      <td>3438.1180</td>\n",
       "      <td>3468.1690</td>\n",
       "      <td>0.011433</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-12</th>\n",
       "      <td>3459.9564</td>\n",
       "      <td>3479.0958</td>\n",
       "      <td>3457.3633</td>\n",
       "      <td>3472.4014</td>\n",
       "      <td>0.001220</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-15</th>\n",
       "      <td>3462.6113</td>\n",
       "      <td>3481.4613</td>\n",
       "      <td>3460.7915</td>\n",
       "      <td>3476.2467</td>\n",
       "      <td>0.001107</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-16</th>\n",
       "      <td>3466.8523</td>\n",
       "      <td>3500.2943</td>\n",
       "      <td>3464.3655</td>\n",
       "      <td>3498.2827</td>\n",
       "      <td>0.006339</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4745 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 open       high        low      close       pct  weekday\n",
       "trade_date                                                               \n",
       "2005-01-04   994.7690   994.7690   980.6580   982.7940       NaN        1\n",
       "2005-01-05   981.5770   997.3230   979.8770   992.5640  0.009941        2\n",
       "2005-01-06   993.3310   993.7880   980.3300   983.1740 -0.009460        3\n",
       "2005-01-07   983.0450   995.7110   979.8120   983.9580  0.000797        4\n",
       "2005-01-10   983.7600   993.9590   979.7890   993.8790  0.010083        0\n",
       "...               ...        ...        ...        ...       ...      ...\n",
       "2024-07-10  3425.8818  3447.5050  3423.6483  3428.9657 -0.003153        2\n",
       "2024-07-11  3451.0442  3473.9837  3438.1180  3468.1690  0.011433        3\n",
       "2024-07-12  3459.9564  3479.0958  3457.3633  3472.4014  0.001220        4\n",
       "2024-07-15  3462.6113  3481.4613  3460.7915  3476.2467  0.001107        0\n",
       "2024-07-16  3466.8523  3500.2943  3464.3655  3498.2827  0.006339        1\n",
       "\n",
       "[4745 rows x 6 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "025e707a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "26"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(dd['high'] + dd['low'] == dd['open'] + dd['close']).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "6483ef1f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='trade_date'>"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(((dd['high'] == dd['open']) & (dd['low'] == dd['close']))*dd['pct'].shift(-1)).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2c837074",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='trade_date'>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(((dd['high'] == dd['close']) & (dd['low'] == dd['open']))*dd['pct'].shift(-1)).cumsum().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "4207246c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>pct</th>\n",
       "      <th>weekday</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>trade_date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2005-01-04</th>\n",
       "      <td>994.7690</td>\n",
       "      <td>994.7690</td>\n",
       "      <td>980.6580</td>\n",
       "      <td>982.7940</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-05</th>\n",
       "      <td>981.5770</td>\n",
       "      <td>997.3230</td>\n",
       "      <td>979.8770</td>\n",
       "      <td>992.5640</td>\n",
       "      <td>0.009941</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-06</th>\n",
       "      <td>993.3310</td>\n",
       "      <td>993.7880</td>\n",
       "      <td>980.3300</td>\n",
       "      <td>983.1740</td>\n",
       "      <td>-0.009460</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-07</th>\n",
       "      <td>983.0450</td>\n",
       "      <td>995.7110</td>\n",
       "      <td>979.8120</td>\n",
       "      <td>983.9580</td>\n",
       "      <td>0.000797</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-10</th>\n",
       "      <td>983.7600</td>\n",
       "      <td>993.9590</td>\n",
       "      <td>979.7890</td>\n",
       "      <td>993.8790</td>\n",
       "      <td>0.010083</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-10</th>\n",
       "      <td>3425.8818</td>\n",
       "      <td>3447.5050</td>\n",
       "      <td>3423.6483</td>\n",
       "      <td>3428.9657</td>\n",
       "      <td>-0.003153</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-11</th>\n",
       "      <td>3451.0442</td>\n",
       "      <td>3473.9837</td>\n",
       "      <td>3438.1180</td>\n",
       "      <td>3468.1690</td>\n",
       "      <td>0.011433</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-12</th>\n",
       "      <td>3459.9564</td>\n",
       "      <td>3479.0958</td>\n",
       "      <td>3457.3633</td>\n",
       "      <td>3472.4014</td>\n",
       "      <td>0.001220</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-15</th>\n",
       "      <td>3462.6113</td>\n",
       "      <td>3481.4613</td>\n",
       "      <td>3460.7915</td>\n",
       "      <td>3476.2467</td>\n",
       "      <td>0.001107</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-16</th>\n",
       "      <td>3466.8523</td>\n",
       "      <td>3500.2943</td>\n",
       "      <td>3464.3655</td>\n",
       "      <td>3498.2827</td>\n",
       "      <td>0.006339</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4745 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 open       high        low      close       pct  weekday\n",
       "trade_date                                                               \n",
       "2005-01-04   994.7690   994.7690   980.6580   982.7940       NaN        1\n",
       "2005-01-05   981.5770   997.3230   979.8770   992.5640  0.009941        2\n",
       "2005-01-06   993.3310   993.7880   980.3300   983.1740 -0.009460        3\n",
       "2005-01-07   983.0450   995.7110   979.8120   983.9580  0.000797        4\n",
       "2005-01-10   983.7600   993.9590   979.7890   993.8790  0.010083        0\n",
       "...               ...        ...        ...        ...       ...      ...\n",
       "2024-07-10  3425.8818  3447.5050  3423.6483  3428.9657 -0.003153        2\n",
       "2024-07-11  3451.0442  3473.9837  3438.1180  3468.1690  0.011433        3\n",
       "2024-07-12  3459.9564  3479.0958  3457.3633  3472.4014  0.001220        4\n",
       "2024-07-15  3462.6113  3481.4613  3460.7915  3476.2467  0.001107        0\n",
       "2024-07-16  3466.8523  3500.2943  3464.3655  3498.2827  0.006339        1\n",
       "\n",
       "[4745 rows x 6 columns]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbb2aeea",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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